In this paper motion of rigid rod on a circular surface is studied analytically.A new analytical method called modified homotopy perturbation method(MHPM)is applied for solving this problem in different initial condit...In this paper motion of rigid rod on a circular surface is studied analytically.A new analytical method called modified homotopy perturbation method(MHPM)is applied for solving this problem in different initial conditions to show capability of this method.The goveming equation for motion of a nigid rod on the circular surface without slipping have been solved using MHPM.The efficacy of MHPM for handling nonlinear oscillation systems with various small and large oscillation amplitudes are presented in comparison with numerical benchmarks.Outcomes reveal that MHPM has an excellent agreement with numerical solution.The results show that by decreasing the oscillation amplitude,the velocity of rigid rod decreases and for A=w3 the velocity profile is maximum.展开更多
Despite its remarkable performance on natural images,the segment anything model(SAM)lacks domain-specific information in medical imaging.and faces the challenge of losing local multi-scale information in the encoding ...Despite its remarkable performance on natural images,the segment anything model(SAM)lacks domain-specific information in medical imaging.and faces the challenge of losing local multi-scale information in the encoding phase.This paper presents a medical image segmentation model based on SAM with a local multi-scale feature encoder(LMSFE-SAM)to address the issues above.Firstly,based on the SAM,a local multi-scale feature encoder is introduced to improve the representation of features within local receptive field,thereby supplying the Vision Transformer(ViT)branch in SAM with enriched local multi-scale contextual information.At the same time,a multiaxial Hadamard product module(MHPM)is incorporated into the local multi-scale feature encoder in a lightweight manner to reduce the quadratic complexity and noise interference.Subsequently,a cross-branch balancing adapter is designed to balance the local and global information between the local multi-scale feature encoder and the ViT encoder in SAM.Finally,to obtain smaller input image size and to mitigate overlapping in patch embeddings,the size of the input image is reduced from 1024×1024 pixels to 256×256 pixels,and a multidimensional information adaptation component is developed,which includes feature adapters,position adapters,and channel-spatial adapters.This component effectively integrates the information from small-sized medical images into SAM,enhancing its suitability for clinical deployment.The proposed model demonstrates an average enhancement ranging from 0.0387 to 0.3191 across six objective evaluation metrics on BUSI,DDTI,and TN3K datasets compared to eight other representative image segmentation models.This significantly enhances the performance of the SAM on medical images,providing clinicians with a powerful tool in clinical diagnosis.展开更多
"第二军医大学军队卫生政策与管理(MILITARY Health Policy and Management,MHPM)研究中心"依托该校军队卫生事 业管理教研室,集成相关研究力量和资源优势,于2004年初获准成立。中心旨在建成一个符合国际惯例专业口径、研究 ..."第二军医大学军队卫生政策与管理(MILITARY Health Policy and Management,MHPM)研究中心"依托该校军队卫生事 业管理教研室,集成相关研究力量和资源优势,于2004年初获准成立。中心旨在建成一个符合国际惯例专业口径、研究 水平居国内领先地位的卫生事业管理辅助决策常设研究机构,以利于形成不间断的卫生政策与管理研究机制。展开更多
文摘In this paper motion of rigid rod on a circular surface is studied analytically.A new analytical method called modified homotopy perturbation method(MHPM)is applied for solving this problem in different initial conditions to show capability of this method.The goveming equation for motion of a nigid rod on the circular surface without slipping have been solved using MHPM.The efficacy of MHPM for handling nonlinear oscillation systems with various small and large oscillation amplitudes are presented in comparison with numerical benchmarks.Outcomes reveal that MHPM has an excellent agreement with numerical solution.The results show that by decreasing the oscillation amplitude,the velocity of rigid rod decreases and for A=w3 the velocity profile is maximum.
基金supported by Natural Science Foundation Programme of Gansu Province(No.24JRRA231)National Natural Science Foundation of China(No.62061023)Gansu Provincial Science and Technology Plan Key Research and Development Program Project(No.24YFFA024).
文摘Despite its remarkable performance on natural images,the segment anything model(SAM)lacks domain-specific information in medical imaging.and faces the challenge of losing local multi-scale information in the encoding phase.This paper presents a medical image segmentation model based on SAM with a local multi-scale feature encoder(LMSFE-SAM)to address the issues above.Firstly,based on the SAM,a local multi-scale feature encoder is introduced to improve the representation of features within local receptive field,thereby supplying the Vision Transformer(ViT)branch in SAM with enriched local multi-scale contextual information.At the same time,a multiaxial Hadamard product module(MHPM)is incorporated into the local multi-scale feature encoder in a lightweight manner to reduce the quadratic complexity and noise interference.Subsequently,a cross-branch balancing adapter is designed to balance the local and global information between the local multi-scale feature encoder and the ViT encoder in SAM.Finally,to obtain smaller input image size and to mitigate overlapping in patch embeddings,the size of the input image is reduced from 1024×1024 pixels to 256×256 pixels,and a multidimensional information adaptation component is developed,which includes feature adapters,position adapters,and channel-spatial adapters.This component effectively integrates the information from small-sized medical images into SAM,enhancing its suitability for clinical deployment.The proposed model demonstrates an average enhancement ranging from 0.0387 to 0.3191 across six objective evaluation metrics on BUSI,DDTI,and TN3K datasets compared to eight other representative image segmentation models.This significantly enhances the performance of the SAM on medical images,providing clinicians with a powerful tool in clinical diagnosis.
文摘"第二军医大学军队卫生政策与管理(MILITARY Health Policy and Management,MHPM)研究中心"依托该校军队卫生事 业管理教研室,集成相关研究力量和资源优势,于2004年初获准成立。中心旨在建成一个符合国际惯例专业口径、研究 水平居国内领先地位的卫生事业管理辅助决策常设研究机构,以利于形成不间断的卫生政策与管理研究机制。
